摘要：
Previous studies have shown that auroral kilometric radiation (AKR) can play an important role in the magnetosphere-atmosphere coupling and has the right-handed extraordinary (R-X), left-handed ordinary (L-O) and left-handed extraordinary (L-X) modes. However, the L-X mode has not been directly observed in the lower latitude magnetosphere yet, probably because of its very limited frequency range. Here, using observations of the Arase satellite on 6 September 2018, we present an AKR event with two distinct bands (8-20 and 300-1000 kHz) around the location: L = 8 and latitude = -37 degrees. The low (high) band is identified as the L-X (R-X) mode based on the polarization and frequency ranges. Simulations of 3-D ray tracing show that most of ray paths with 14 (11 and 18) kHz pass (miss) the location of Arase, basically consistent with observations. Our study provides direct evidence that the L-X mode can propagate from high latitudes downward to lower latitudes. Auroral kilometric radiation (AKR) is a widely existing radio emission with kilometric wavelength at the Earth, contributing to the magnetosphere-atmosphere coupling. Similar emissions have been observed on all magnetic planets of the solar system. Previous studies have shown that AKR primarily occurs in the R-X mode, with a small contribution in the L-O and L-X modes. The L-X mode at lower latitudes has not been directly observed so far, most likely due to its extremely limited frequency range. Here, we present an L-X mode (peak frequency similar to 14 kHz) in the lower latitude magnetosphere observed by the Arase satellite. Using the 3-D ray tracing method, we simulate ray paths with different initial wave parameters and source locations. Simulations show that ray paths with 14 (11 and 18) kHz pass (miss) the location of the Arase satellite and are highly dependent on initial wave parameters and the location of source. Our results provide a direct evidence that the L-X mode from high latitude source regions can propagate downward to lower latitudes under suitable conditions. This study enriches the understanding of AKR propagation characteristics in the magnetosphere. An auroral kilometric radiation (AKR) event with two distinct bands (8-20 kHz and 300-1000 kHz) is observed around the location: L = 8 and latitude = -37 degrees Based on the polarization and frequency ranges, the low (high) band AKR is identified as the L-X (R-X) mode 3-D ray tracing simulations show that L-X mode can propagate downward to lower latitudes, basically consistent with observations
通讯机构：
[Xu, XD ] C;Cent South Univ, Sch Automat, Changsha 410017, Peoples R China.;Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 2R3, Canada.
关键词：
Adaptive boundary vibration controller;disturbance observer network;Euler-Bernoulli beam equation;multiagent system
摘要：
This article presents a method for the vibration suppression problem of a network of multiagent Euler-Bernoulli beams whose dynamics are governed by fourth-order partial differential equations (PDEs). Particularly, the considered multiagent systems are subjected to unknown external disturbances causing unexpected vibration. To this end, this article develops an adaptive vibration controller to reject unknown disturbances and achieve vibration suppression. The proposed controller is equipped with a novel network of cooperative boundary disturbance observers, and each observer in the network transmits the estimated disturbance information. The cooperation among the observers in the network guides to achieve observation consensus. Moreover, based on the proposed disturbance observer network, a new antivibration adaptive boundary controller is developed, and the closed-loop stability is proved based on Lyapunov theory. In addition, it is also shown theoretically that the proposed controller is robust to unknown spatiotemporally distributed load. To validate the effectiveness of the proposed method, numerical simulation examples are carried out, and the application on a marine riser system is studied to further show the strength of the proposed method.
作者机构：
[Peng, Shurong; Liu, Xiaoxu] Shenzhen Technol Univ, Sino German Coll Intelligent Mfg, Shenzhen 518118, Peoples R China.;[Huang, Haoyu; Guo, Lijuan; Li, Yuanshu] Changsha Univ Sci Technol, Sch Elect & Informat Engn, Changsha 410114, Peoples R China.;[Peng, Jiayi; Peng, JY] State Grid Hunan Power Co, State Grid Zhuzhou Power Supply Co, Zhuzhou 412011, Peoples R China.
通讯机构：
[Peng, JY ] S;State Grid Hunan Power Co, State Grid Zhuzhou Power Supply Co, Zhuzhou 412011, Peoples R China.
关键词：
ensemble learning;kitchen waste power generation;biogas prediction;features correlation analysis;K-fold cross-validation
摘要：
The allocation of biogas between power generation and heat supply in traditional kitchen waste power generation system is unreasonable; for this reason, a biogas prediction method based on feature selection and heterogeneous model integration learning is proposed for biogas production predictions. Firstly, the working principle of the biogas generation system based on kitchen waste is analyzed, the relationship between system features and biogas production is mined, and the important features are extracted. Secondly, the prediction performance of different individual learner models is comprehensively analyzed, and the training set is divided to reduce the risk of overfitting by combining K-fold cross-validation. Finally, different primary learners and meta learners are selected according to the prediction error and diversity index, and different learners are fused to construct the stacking ensemble learning model with a two-layer structure. The experimental results show that the research method has a higher prediction accuracy in predicting biogas production, which provides supporting data for the economic planning of kitchen waste power generation systems.
摘要：
随着新能源并网进程的推进,风电装机规模逐年扩大。受区域内天气变化影响,风机出力的间歇性和波动性特征对电网的威胁亦越发显著。极端天气所引发的风电出力异常爬坡事件,易导致电网功率失衡,对电力系统机组调度、源荷平衡造成了极大压...展开更多 随着新能源并网进程的推进,风电装机规模逐年扩大。受区域内天气变化影响,风机出力的间歇性和波动性特征对电网的威胁亦越发显著。极端天气所引发的风电出力异常爬坡事件,易导致电网功率失衡,对电力系统机组调度、源荷平衡造成了极大压力。合理的风电爬坡事件检测以及精准的风电功率预测能为风电场运维及电力系统调度提供先验指导,有力缓解风电不确定性带来的危害。首先讨论了目前主流风电爬坡事件定义的盲点,分类并分析了3种风电爬坡场景的功率变化特性,据此提出基于滑动窗双边累计和(cumulative sum, CUSUM)算法的风电爬坡事件检测方法,提取时序耦合信息,捕捉短时间窗口内风电功率数据的异常波动,提高风电爬坡事件检测精度。其次,采用贝叶斯优化的长短期记忆(long short term memory, LSTM)神经网络,最优化模型超参数,提高模型对于爬坡事件发生时风机出力的预测性能。进一步应用所提风电爬坡事件检测方法,对模型预测区间内的风电爬坡事件进行检测实验,验证了所提方法的有效性。收起
期刊：
Frontiers in Energy Research,2024年11:1293192 ISSN：2296-598X
通讯作者：
Su, S
作者机构：
[Xia, Yunfeng] Hainan Power Grid Co Ltd, Hainan Power Transmiss & Transformat Maintenance B, Haikou, Peoples R China.;[Li, Bin; Su, Sheng; Zhou, Xuan] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha, Peoples R China.
通讯机构：
[Su, S ] C;Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha, Peoples R China.
关键词：
lightning;joint distribution;wind speed;Transmission system;Lightning location system (LLS)
摘要：
Distribution of lightning plays a key role in lightning protection of transmission lines. The design of wind deviation under lightning overvoltage of the transmission tower is an empirical parameter in the transmission line design code. Meteorological data from Hong Kong are investigated to analyze the joint distribution of lightning and wind speed. It has been uncovered that daily cloud-to-ground (CG) flashes follow the Burr distribution, which is highly skewed toward a few days with notable lightning. The lightning and wind follow a Gumbel copula joint distribution. According to empirical and theoretical distribution, there are 239 days with more than 1,000 CG lightning flashes per day, and approximately 20% of these days have a maximum wind speed of approximately or over 15 m/s. In 5 days with the number of CG lightning flashes above 30,000, 3 days have a maximum wind speed of over 15 m/s and the other 2 days have a maximum wind speed of over 10 m/s, which suggests that the severe convection with a squall line contributes much to the likelihood of the days with high wind and lightning storms.
作者机构：
[Peng, Shurong; Liu, Xiaoxu] Shenzhen Technol Univ, Sino German Coll Intelligent Mfg, Shenzhen 518118, Peoples R China.;[Peng, Shurong; Huang, Haoyu; Guo, Lijuan] Changsha Univ Sci Technol, Sch Elect & Informat Engn, Changsha 410114, Peoples R China.;[Peng, Jiayi; Peng, JY] State Grid Zhuzhou Power Supply Co, State Grid Hunan Power Co, Zhuzhou 412011, Peoples R China.
通讯机构：
[Peng, JY ] S;State Grid Zhuzhou Power Supply Co, State Grid Hunan Power Co, Zhuzhou 412011, Peoples R China.
关键词：
time-variant deep feed-forward neural network;probability density prediction;spatio-temporal distribution
摘要：
The integration of large-scale wind power into the power grid threatens the stable operation of the power system. Traditional wind power prediction is based on time series without considering the variability between wind turbines in different locations. This paper proposes a wind power probability density prediction method based on a time-variant deep feed-forward neural network (ForecastNet) considering a spatio-temporal distribution. First, the outliers in the wind turbine data are detected based on the isolated forest algorithm and repaired through Lagrange interpolation. Then, based on the graph attention mechanism, the features of the proximity node information of the individual wind turbines in the wind farm are extracted and the input feature matrix is constructed. Finally, the wind power probability density prediction results are obtained using the ForecastNet model based on three different hidden layer variants. The experimental results show that the ForecastNet model with a hidden layer as a dense network based on the attention mechanism (ADFN) predicts better. The average width of the prediction intervals at achieved confidence levels for all interval coverage is reduced by 34.19%, 35.41%, and 35.17%, respectively, when compared to the model with the hidden layer as a multilayer perceptron. For different categories of wind turbines, ADFN also achieves relatively narrow interval average widths of 368.37 kW, 315.87 kW, and 299.13 kW, respectively.
摘要：
Abstract With the widespread application of composite insulators in transmission lines, exploring the accumulation mechanism of pollution particles on composite insulator surfaces is of importance to ensure the safe and steady operation of the power system. Addressing the current theoretical shortcomings, this study categorises the accumulation process of particles on the insulator surface into three stages, namely ‘spatial motion’, ‘surface collision’, and ‘surface motion’. The motion and rotation velocities in a multi‐physics field are calculated in the spatial motion stage. In the surface collision stage, a parameter called ‘neck height’ is introduced to determine the optimum mechanics theory, and the normal deposition criterion is established. For the surface motion stage, the sliding displacement and rolling displacement on the surface are calculated based on the rotation speed of the particles. A dynamic pollution accumulation model of the composite insulator is established based on the normal deposition criterion and tangential displacement. Finally, numerical simulations are performed by using the finite element method. Simulation results show that the proposed model agrees with the actual insulator pollution accumulation, and the deposition model is still applicable for various types of composite insulators operating in different applied voltages. The deposition probability of particles increases with the increasing particle size. In the surface motion stage, particle displacement increases with particle size and wind velocity.
期刊：
Journal of Electrical Engineering & Technology,2024年:1-14 ISSN：1975-0102
通讯作者：
Wen Wang
作者机构：
[Chuanping Wu; Tiannian Zhou; Yu Liu] Hunan Electric Power Corporation Disaster Prevention and Reduction Center, Changsha, China;[Huaze Shi] CHN Energy Hunan Electricity Power New Energy Co., Ltd, Changsha, China;[Yixuan Feng; Wen Wang] School of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha, China
通讯机构：
[Wen Wang] S;School of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha, China
关键词：
Ultracapacitor;State of charge;Adaptive unscented Kalman filter;Sage-Husa;Joint SOC estimation
摘要：
In the field of new energy electric vehicles, ultracapacitor modules are often used as energy storage batteries. Precise estimation of state of charge (SOC) of ultracapacitor modules is critical to the secure operation of vehicle power supply. In this paper, equivalent circuit models and SOC estimation algorithms are compared and analyzed. The forgetting factor recursive least squares (FFRLS) is employed to supply precise equal circuit model parameters for SOC estimation algorithm. On this basis, an improved Sage-Husa adaptive unscented Kalman filter (IAUKF) online SOC estimation algorithm is proposed. The improved unscented Kalman filter algorithm solves the problems of poor robustness and large computational effort of the conventional Sage-Husa adaptive unscented Kalman filter algorithm (AUKF). The experiment verification is carried out in UDDS test and FUDS test respectively. The experiment verified that the SOC estimation error of IAUKF algorithm is less than 1.076%, and the average relative error is reduced by more than 50.574% compared with the conventional algorithms. The FFRLS-IAUKF joint SOC estimation algorithm has high estimation accuracy and good robustness.
摘要：
The presence of unknown heavy-tailed noise can lead to inaccuracies in measurements and processes, resulting in instability in nonlinear systems. Various estimation methods for heavy-tailed noise exist. However, these methods often trade estimation accuracy for algorithm complexity and parameter sensitivity. To tackle this challenge, we introduced an improved variational Bayesian (VB)-based adaptive iterative extended Kalman filter. In this VB framework, the inverse Wishart distributionis used as the prior for the state prediction covariance matrix. The system state and noise parameter posterior distributions are then iteratively updated for adaptive estimation. Furthermore, we make adaptive adjustments to the IEKF filter parameters to enhance sensitivity and filtering accuracy, thus ensuring robust prediction estimation. A two-dimensional target tracking and nonlinear numerical UNGM simulation validated our algorithm. Compared to existing algorithms RKF-ML and GA-VB, our method showed significant improvements in RMSEpos and RMSEvel, with increases of 21.81% and 22.11% respectively, and a 49.04% faster convergence speed. These results highlight the method's reliability and adaptability.
摘要：
As large-scale lithium-ion battery energy storage power facilities are built, the issues of safety operations become more complex. The existing difficulties revolve around effective battery health evaluation, cell-to-cell variation evaluation, circulation, and resonance suppression, and more. Based on this, this paper first reviews battery health evaluation methods based on various methods and summarizes the selection of existing health factors in data-driven methods. Secondly, the paper discusses the new research hotspots in the existing battery state evaluation technologies from the perspectives of state evaluation using data fragments and edge computing. Thirdly, we focus and discuss on the safety operation technologies of energy storage stations, including the issues of inconsistency, balancing, circulation, and resonance. To address these issues, we present an intelligent inspection robot, enabling real-time data interaction with the EMS and fulfilling rapid inspection and real-time diagnosis. Above all, we focus on the safety operation challenges for energy storage power stations and give our views and validate them with practical engineering applications, building the foundation of the next-generation techniques that support the development of new power systems.
摘要：
Developing efficient defensive strategies against cyber-attacks is a major concern of modern power system research. With the goal of minimizing the expected load loss, this article proposes a robust probabilistic substation-based defender-attacker-defender (DAD) model to allocate the substation's defensive resources. The proposed model aims to minimize the risk of cyber-attacks on intelligent electronic devices (IEDs). The game between the defender and the attacker concerning multiple substations, IEDs, and their connected lines is particularly modeled. In addition, we extend the proposed probabilistic DAD model to an observability-ensured DAD model where the existing phasor measurement units in the power grids are considered in the defensive resource allocation. Integrated with the logarithmic transformation and piecewise linearization techniques, a customized column-and-constraint generation algorithm is developed to solve the proposed model. Finally, the numerical results on IEEE RTS 24-bus and 118-bus systems validate the proposed model.
摘要：
双碳政策推动下，乡村农业综合能源系统（integrated energy system，IES）的多能耦合关系更加复杂。为实现农业园区可靠运行，提出面向生态农业IES的多能互补与低碳运行优化调度策略。首先，基于农业园区的能量流动关系，建立沼气生产环节、多能耦合供应环节以及柔性负荷需求响应环节的数学模型。其次，考虑光伏、负荷和沼气的不确定性，建立生态农业IES两阶段鲁棒优化模型。模型引入碳排放成本和启停成本，可降低农业生产碳排放，防止机组频繁启停。然后，采用列与约束生成算法（column-and-constraint generation，C＆CG），结合强对偶定理与线性化理论实现模型求解。最后，基于江西省某生态牧场IES进行算例仿真，验证所提策略的有效性。仿真结果表明，所提策略可实现生态农业IES的协调运行，提高系统经济性、低碳性和能效性。
摘要：
This article investigates the adaptive neural tracking control problem for a class of hyperbolic PDE with boundary actuator dynamics described by a set of nonlinear ordinary differential equations (ODEs). Particularly, the control input appears in the ODE subsystem with unknown nonlinearities requiring to be estimated and compensated, which makes the control task rather difficult. It is the first time to consider tracking control of such a class of systems, rendering our contributions essentially different from the existing literature that merely focus on the stabilization problem. By formulating a virtual exosystem to generate a reference trajectory, we propose a novel design of the adaptive geometric controller for the considered system where neural networks (NNs) are employed to approximately estimate nonlinearities, and finite and infinite-dimensional backstepping techniques are leveraged. Moreover, rigorously theoretical proofs based on the Lyapunov theory are provided to analyze the stability of the closed-loop system. Finally, we illustrate the results through two numerical simulations.
期刊：
International Journal of Electrical Power & Energy Systems,2024年156:109749 ISSN：0142-0615
通讯作者：
Jiao, H
作者机构：
[Li, Chengjin; Xiao, Jun; Jiao, Heng; Zu, Guoqiang] Tianjin Univ, Key Lab Smart Grid, Educ Minist, Tianjin 300072, Peoples R China.;[Zu, Guoqiang] Changsha Univ Sci Technol, Sch Elect & Informat Engn, Changsha 410114, Peoples R China.;[Zu, Guoqiang] State Grid Tianjin Elect Power Res Inst, Tianjin 300384, Peoples R China.;[Cai, Zhongwei] North Sub Ctr State Grid Customer Serv Ctr, Tianjin 300309, Peoples R China.;[She, Buxin] Univ Tennessee, Dept Elect Engn & Comp Sci, Knoxville, TN 37996 USA.
通讯机构：
[Jiao, H ] T;Tianjin Univ, Key Lab Smart Grid, Educ Minist, Tianjin 300072, Peoples R China.
关键词：
Distribution system;Judgment theorem;N-1;Security boundary
摘要：
Security boundary characterizes the operations range of a distribution system satisfying N-1 security, and this paper proposes three judgment theorems for it. Firstly, the relevant concepts of the security boundary are introduced. The security boundary represents the set of all the critical secure operating points in the state space of a distribution system. Based on the degree of criticality, it can be classified into two types, i.e., strict and non-strict boundaries. Secondly, the load relationships between interconnected feeders are defined, and based on this, three judgment theorems are proposed. Thirdly, the proposed theorems are rigorously proven. Finally, an IEEE RBTS test system is used to verify the proposed theorems and demonstrate their applications. The proposed theorems enable convenient judgment of whether an operating point is a security boundary point and its type. This work reveals the load distribution characteristics of security boundary points, providing fundamental contributions to security boundary theory.
期刊：
IEEE INTERNET OF THINGS JOURNAL,2024年11(3):4668-4678 ISSN：2327-4662
作者机构：
[Yinqiang Deng] School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, China;[Yong Liao] School of Physics, Electronics and Electrical Engineering, Xiangnan University, Chenzhou, China;[Xu Wang] School of Automation, Guangdong University of Technology, Guangzhou, China
摘要：
Electric load forecasting (ELF) is always employed to perform power systems management. However, it is difficult to predict electric load due to the following issues: 1) electric load prediction is prone to external interference, e.g., temperature and weather; 2) the user behaviors are random, such as family gatherings and business rush orders; and 3) electric load consumption varies significantly in different time periods. To solve such problems, an adaptive sparse attention network (ASA-Net) is proposed for ELF, where the adaptive sparse spatial attention (ASSA) module is first designed to increase the anti-interference ability by capturing the detail change caused by external interference; next, the adaptive sparse channel attention (ASCA) module is developed to enhance the tolerance to local outliers by learning their feature information; and finally, the adaptive sparse batch attention (ASBA) module is devised to model the dependencies of the timestamp to reduce the time impact on ELF. Experiments conducted on the benchmarks show the excellent performance of ASA-Net for ELF, and it can further provide valuable assistance for the smart grid.
期刊：
IEEE Transactions on Power Systems,2024年39(2):2461-2474 ISSN：0885-8950
作者机构：
[Weiyu Wang; Yijia Cao; Chun Chen; Shuaihu Li; Xingyu Shi] School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, China;[Lin Jiang] Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, U.K.;[Yong Li] College of Electrical and Information Engineering, Hunan University, Changsha, China
摘要：
Low-inertia power grids could suffer from large frequency excursions under even small power disturbances. When a voltage source converter-based high voltage direct current (VSC-HVDC) system is used to integrate a low-inertia grid into a main grid, an ancillary frequency support service can be provided to the low-inertia grid by the VSC-HVDC system. This paper proposes a perturbation observer-based fast frequency support controller (POFFS) of VSC-HVDC systems to improve the frequency stability of low-inertia power grids. According to the feedback linearization and the high gain observer technique, the perturbation observer of the inverter station is designed to estimate the comprehensive impact of multiple perturbations, including the power disturbances in low-inertia grids, the uncertainty of grid inertia, and unknown nonlinear dynamics. The estimate of the perturbations are further compensated by the feedback control loop to achieve robust frequency regulation. Compared with the conventional frequency controller, the proposed POFFS can provide better frequency support to low-inertia power grids, without requiring an accurate system model and parameters. Two test systems are used to verify the effectiveness of the proposed POFFS.
通讯机构：
[Xu, XD ] C;Cent South Univ, Sch Automat, Changsha 410083, Peoples R China.;Cent South Univ, Key Lab Ind Intelligence & Syst, Changsha 410083, Peoples R China.;Univ Alberta, Chem & Mat Engn, Edmonton, AB, Canada.
关键词：
Sliding mode control;Fault-tolerant control;Euler–Bernoulli beam;Event-triggered control
摘要：
In this article, a robust fault-tolerant sliding mode controller is proposed for a class of non-homogeneous Euler-Bernoulli beams which contains controller time-varying fault, external unknown spatiotemporally varying disturbance, and parametric uncertainties. Furthermore, to reduce the number of correspondence between the controller and the actuator, two event-triggered mechanisms are incorporated into the controller design. The sliding surface designed ensures that the system is uniformly ultimately bounded and robust to the parameter uncertainties in model. In addition, the Euler-Bernoulli beam can be used as a model for the flexible wind turbine tower. Numerical simulations are shown to illustrate the validity and effectiveness of the proposed control method. The simulation results show that in the presence of unknown faults and parametric uncertainties, the proposed controller can still effectively suppress the vibration of the tower, while the event-triggered mechanism significantly reduces the communications burden.
摘要：
Abstract This work develops a network of adaptive boundary observers and studies the agreement between state and parameter estimates for a single target parabolic partial differential equation (PDE) system in the presence of structured and unstructured uncertainties. It is assumed that the unknown parameters take the form of either a structured uncertainty with unknown constant parameters or an unstructured uncertainty that can be neutralized by a radial basis function neural networks with unknown weights. The proposed adaptive observers consisting of m$$ m $$ agents in the network follow the structure of adaptive identifiers for the considered target PDE systems with the insertion of a penalty term in both the state and parameter estimates. Different from earlier efforts, the proposed adaptive laws include a penalty term of the mismatch between the parameter and state estimates generated by the other adjacent agents, which helps to accelerate the estimation of uncertainties. Additionally, the effects of these modifications on the agreement amongst the state and parameter estimates are investigated. Theoretical proofs are provided to show that the proposed approach guarantees the exponential convergence of estimation errors in the case of structured uncertainties and the ultimate boundedness of estimation errors in the case of unstructured uncertainties. Finally, numerical simulations are carried out to verify the effectiveness of the design methods.
